Integer and Constraint Programming for the Offline Nanosatellite Partition Scheduling Problem

Julien Rouzot, Mickaël Pereira, Christian Artigues, Romain Boyer, Frédéric Camps, Philippe Garnier, Emmanuel Hebrard, Pierre Lopez

Abstract: Effective scheduling of tasks for nanosatellites is essential, given their limited onboard resources and capabilities. In a typical nanosatellite mission, the onboard computer has to run payload tasks linked to the mission objective, such as observations and measurements for science campaigns, but also communication and avionic tasks needed for navigation and safety. We consider a partitioned real-time system where a partition is a job that embeds a set of elementary tasks implementing one of the above-described functions. The offline nanosatellite partition scheduling problem consists in scheduling a set of partitions on a singlecore processor within a fixed time frame that will be repeated cyclically, while maximizing the number and duration of scheduled payload partitions. The paper first establishes similarities and differences with related scheduling problems. We then prove that the problem is strongly NP-hard. A Mixed Integer Linear Programming (MILP) matheuristic and a Constraint Programming (CP) model are proposed. We compare the MILP and CP approaches in a multi-objective context and demonstrate the relevance of the latter to solve the problem efficiently both on randomly generated instances and on a real nanosatellite case study of the University Space Center of Toulouse: the NIMPH project. The CP model is embedded in NanoSatScheduler, an open source software with a user interface designed for the offline nanosatellite partition scheduling problem. For the NIMPH real-case study, the proposed solution outperforms the semi-manual approach used so far. As a result, the NIMPH team has adopted NanoSatScheduler as an operational tool for their mission.

External IDs:dblp:conf/cpaior/RouzotPABCGHL25